The analysis of dissipative, autonomousThe framework can also be applied to nonautonomous flows, as far as their explicit time-dependence can be regarded as slow in comparison with the relaxation times toward the system's attractors (adiabatic approximation). dynamic flows (especially high-dimensional ones) can be greatly simplified, if a function can be constructed to provide an “energy landscape” to the problem. Energy landscapes not only help visualize the systems' phase space and its structural changes as parameters are varied, but allow predicting the rates of activated processes [1]}, [2]}, [3]}. Some fields that benefit from the energy landscape approach are optimization problems [4]}, neural networks [5]}, protein folding [6]}, cell nets [7]}, gene regulatory networks [8]}, [9]}, ecology [10]}, and evolution [11]}.
